Dienstag, 2. April 2019, 11:00–11:15, H6

We consider an open quantum system of ultracold Rydberg atoms. The system part consists of resonant dipole-dipole-interacting Rydberg states. The environment part is formed by ’three-level atoms’: each atom has a ground state, a short-lived excited state, and a Rydberg state that interacts with the system states. The two transitions in the environment atoms are optically driven, and provide control over the environment dynamics [1]. Appropriate choice of the laser parameters allows us to prepare a Boltzmann distribution of the system’s eigenstates. By tuning the laser parameters and system-environment interaction, we can change the temperature associated with this Boltzmann distribution, and also the thermalization dynamics [2].
The correct parameters are obtained via machine-learning techniques [3].
Our method provides novel opportunities for quantum simulation of thermalization dynamics using ultracold Rydberg atoms.